Graphics Processor-Based Implementation of Bioinformatics Codes
Our system contains two GPUs, capable of working in parallel, for a total of 256 processors (for comparison, a modern desktop will have two or four processors). Our plan includes using this computational power to improve the performance of existing bioinformatics codes, specifically, the Smith-Waterman algorithm for finding DNA or protein sequence alignment.
Faculty Mentors: Greg Wolfe and Christian Trefftz, Computer Science
Andrew took First Place at the Student Research Competition of the Consortium for Computer Science in Colleges Midwest Conference Sept. 27-18, 2008.
Andrew presented at the ACM/IEEE Supercomputing Conference November 15-21, 2008 in
Andrew can be seen on YouTube talking about his project.
Page last modified March 24, 2014